1. Field of the Invention
The present invention relates to an image processing apparatus and an image processing method. More particularly, the present invention relates to an image processing apparatus and an image processing method for use in recursive processing for noise reduction.
2. Description of the Related Art
X-ray fluoroscopic images are taken at very low X-ray doses in view of radiation exposure adverse-effects. Accordingly, much quantum noise is superposed on the taken X-ray fluoroscopic images. Hitherto, noise reduction has been achieved by applying recursive filtering to perform smoothing of pixels in a time direction, since spatial smoothing processing is not sufficient to remove the noise. The recursive filtering (also referred to as interframe noise reduction processing) is very effective in reducing noise in a plurality of still images. However, when the recursive filtering is applied to moving images, image lags can be generated. Therefore, the recursive filter is not always effective in reducing noise in moving images.
Thus, Japanese Patent Application Laid-Open No. 1-273487 discusses a digital X-ray apparatus capable of displaying a clear image with less image lag in which noise is sufficiently reduced in a case where recursive filtering is performed on a moving image or a continuous image. This digital X-ray apparatus has a separation circuit unit, a filter circuit unit, and an addition circuit unit to achieve noise reduction processing with a reduced image lag. The separation circuit unit separates each frame of an X-ray fluoroscopic image into a low-frequency component image and a high-frequency component image. The filter circuit unit performs recursive filtering on the high-frequency component image. This addition circuit unit adds the separated low-frequency component image to the high-frequency component image on which the recursive filtering has been performed.
Japanese Patent No. 3158371 discusses a noise reducer for reducing noise which extracts a noise signal from a difference signal generated by a difference between a moving image reproduced by an analog video tape recorder and an image obtained by a recursive filter, and subtracts the extracted noise signal from the reproduced moving image. This noise reducer detects motion of an image with a simple method, and changes a reduced amount of noise between the moving image and a still image. Consequently, the noise reducer performs noise reduction processing with less image lag. FIG. 13 illustrates a configuration of a conventional interframe noise reduction unit for recursive filtering. As illustrated in FIG. 13, the interframe noise reduction unit includes a frame memory 1301, subtracters 1302 and 1304, and a nonlinear processing unit 1303.
The frame memory 1301 stores results of noise reduction. The result of noise reduction stored in the frame memory 1301 is delayed by one frame and used as a reference image for performing noise reduction processing on the next input frame image. The subtracter 1302 subtracts the reference image which is supplied from the frame memory 1301 from the input frame image input thereto, and outputs a result of the subtraction to the nonlinear processing unit 1303.
The nonlinear processing unit 1303 performs nonlinear processing on the result of the subtraction (a difference signal) obtained from the subtracter 1302 to extract noise signals having small amplitudes. The subtracter 1304 performs noise reduction on the input frame image by subtracting the noise signals which are extracted by the nonlinear processing unit 1303 from the input frame image. Then, the subtracter 1304 outputs results of the noise reduction which are stored in the frame memory 1301.
Generally, in the interframe noise reduction processing, an amount of noise reduction has an inverse relationship with a blur of movement of an object. When the amount of noise reduction is increased in the interframe noise reduction processing, a moving object is likely to be blurred. On the other hand, when blur of a moving object is to be reduced, it is necessary to decrease the amount of noise reduction.
In the interframe noise reduction unit illustrated in FIG. 13, when the amount of noise reduction is decreased to reduce the blur due to movement of an object in a noise-reduced image, a frame image containing much residual noise becomes a reference image without reducing much noise. This phenomenon adversely affects noise reduction of the next input frame image.
The influence of residual noise on the noise reduction processing is described hereinafter. FIGS. 14A to 14E illustrate results of interframe noise reduction of an input image in a case where a reference image contains no noise. FIGS. 15A to 15E illustrate results of interframe noise reduction of an input image in a case where a reference image contains residual noise.
In the case illustrated in FIGS. 14A to 14E, the reference image contains no noise. Thus, it is supposed that the amplitude level of the reference image is constant without varying (for simplicity of description, amplitude levels at pixels of each of the images are disregarded), as illustrated in FIG. 14A. When the input image containing noise illustrated in FIG. 14B is input, the difference in amplitude level at each pixel between the input image and the reference image illustrated in FIG. 14A is obtained by the subtracter 1302 as a difference signal illustrated in FIG. 14C.
The nonlinear processing unit 1303 extracts only signals, the amplitude level of which is equal to or less than a predetermined threshold value (Th), from the difference signal illustrated in FIG. 14C as noise. Thus, the nonlinear processing unit 1303 obtains signals illustrated in FIG. 14D. All amplitude levels of a signal 1401 on a left side of FIG. 14C are equal to or lower than the threshold value (Th). Accordingly, the signal 1401 is entirely extracted by the nonlinear processing unit 1303. On the other hand, a signal 1402 on a right side of FIG. 14C, has portions whose amplitude level is equal to or lower than the threshold value (Th) and whose amplitude level is higher than the threshold value (Th). Thus, only the portions whose amplitude level is equal to or lower than the threshold value (Th) of the signal 1402 are extracted by the nonlinear processing unit 1303.
The nonlinear processing including such extraction can be easily implemented using a look-up table having an input/output characteristics illustrated in FIG. 16. The input/output characteristics illustrated in FIG. 16 is adapted to the nonlinear processing unit 1303 to pass a signal whose absolute value of the amplitude level is equal to or lower than the threshold value (Th) as it is, and to cut off a signal whose absolute value of the amplitude level is higher than the threshold value (Th) to zero. The threshold value (Th) is determined so as to cover a sufficiently large range of noise distribution. For convenience of description, only an outline of the nonlinear processing is described herein. Thus, a graph of the input/output characteristics illustrated in FIG. 16 has a simple shape. However, if the input/output characteristics illustrated in FIG. 16 is used without change, noise having an amplitude level which is equal to or higher than the threshold value (Th) is fixed and is not attenuated. Therefore, actually used input/output characteristics have a complex shape.
A signal (noise component) illustrated in FIG. 14D is subtracted from a signal representing the input image illustrated in FIG. 14B by the subtracter 1304 and the obtained signal is output to an external device as a result of the noise reduction as illustrated in FIG. 14E. As above-described, the result of the noise reduction is stored in the frame memory 1301 and is used as a reference image for performing the noise reduction on the next input frame image. FIGS. 14A to 14E illustrate that although noise whose amplitude level is higher than the threshold value (Th) in the input frame image cannot be eliminated, noise whose amplitude level is equal to or lower than the threshold value (Th) can be clearly eliminated.
In the case illustrated in FIGS. 15A to 15E, the reference image contains residual noise. As is understood from the foregoing description, noise is left in the reference image in a case where the amplitude level of the noise is higher than the threshold value (Th). Thus, it is supposed in the reference image illustrated in FIG. 15A that two large noise events 1501 and 1502 remain, and that on the other hand, only one noise 1503 having a small amplitude is present in the input image at a location corresponding to the large noise 1502 illustrated in FIG. 15A. In order to illustrate that results of nonlinear processing are different on a left side half and on a right side half of a waveform of a noise, the waveform of the noise 1503 is not laterally symmetric and the amplitude of the left side half thereof is larger than the amplitude of the right-side half thereof, as viewed in FIG. 15B.
The subtracter 1302 obtains a difference in amplitude level at each pixel between an input image illustrated in FIG. 15B and the reference image illustrated in FIG. 15A as a difference signal illustrated in FIG. 15C. The difference signal has a negative polarity as illustrated in FIG. 15C, in contrast to the examples illustrated in FIGS. 14A to 14E. However, when a polarity of each noise in the reference image and the input image is reversed, also the polarity of the difference signal is reversed. Thus, the polarity of the signal is insignificant.
The nonlinear processing unit 1303 extracts only signals whose amplitude level is equal to or less than a predetermined threshold value (Th) from the difference signal illustrated in FIG. 15C as noise. Thus, the nonlinear processing unit 1303 obtains signals illustrated in FIG. 15D. A signal (noise component) illustrated in FIG. 15D is subtracted from a signal representing the input image illustrated in FIG. 15B by the subtracter 1304 and the obtained signal is output to an external device as a result of the noise reduction illustrated in FIG. 15E. Further, the result of the noise reduction is stored in the frame memory 1301 and is used as a reference image for performing the noise reduction on the next input frame image.
If noise is left in the reference image as illustrated in FIGS. 15A through 15E, noise is extracted to an output of the nonlinear processing unit 1303 which corresponds to a portion containing no noise in the input image, as illustrated in FIG. 15D. The extracted noise is subtracted from the input image. Thus, as illustrated in FIG. 15E, the extracted noise is superposed on the noise-reduced output of the nonlinear processing unit 1303. That is, the residual noise within a certain range of amplitude level still remains as the residual noise in the next frame. Moreover, an input noise is affected by residual noise in a case where the residual noise is present at a pixel of the reference image and consequently, substantially no effects of reducing noise are obtained. In addition, residual noises can further easily remain in the reference image.
If interframe noise reduction is applied to each image generated by multiresolution analysis for decomposing an image into sub-images corresponding to a plurality of frequency bands, blur due to movement of a moving object can be mitigated by adjusting the amount of noise reduction in each sub-image according to an associated one of the frequency bands. However, when the amount of noise reduction is increased, a problem that an area with movement is blurred still remains.
Accordingly, it is necessary for reducing the blur caused by the movement to lower the degree of noise reduction. However, residual noise is increased in a frame image if the degree of noise reduction performed on the image is lowered. If the frame image of a low degree of noise reduction is used as a reference image for noise reduction of the next frame image, noise in a pixel including residual noise is not reduced. In addition, residual noise can easily remain. That is, a conventional noise reduction method has a drawback that in a case where an amount of noise reduction in an output image is decreased by preferentially reducing a blur and an image lag caused by movement of a moving object, while a blur caused by movement of an object is reduced in a current frame image, effects of noise reduction of the next frame image are reduced.